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Granular Income Inequality and Mobility using IDDA: Exploring Patterns across Race and Ethnicity

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  • Natalie Gubbay
  • Brandon Hawkins
  • Illenin O. Kondo
  • Kevin Rinz
  • John Voorheis
  • Abigail Wozniak

Abstract

We explore the evolution of income inequality and mobility in the U.S. for a large number of subnational groups defined by race and ethnicity, using granular statistics describing income distributions, income mobility, and conditional income growth derived from the universe of tax filers and W-2 recipients that we observe over a two-decade period (1998–2019). We find that income inequality and income growth patterns identified from administrative tax records differ in important ways from those that one might identify in public survey sources. The full set of statistics that we construct is available publicly alongside this paper as the Income Distributions and Dynamics in America, or IDDA, dataset. Using two applications, we illustrate IDDA’s relevance for understanding income inequality trends. First, we extend Bayer and Charles (2018) beyond earnings gaps between Black and White men and document that, unlike those for other groups, earnings for both Black men and Black women fell behind earnings for White men following the Great Recession. This trend lasted through 2019, the end of the data period. Second, we document a significant reversal in the convergence of earnings for Native earners in Native areas.

Suggested Citation

  • Natalie Gubbay & Brandon Hawkins & Illenin O. Kondo & Kevin Rinz & John Voorheis & Abigail Wozniak, 2024. "Granular Income Inequality and Mobility using IDDA: Exploring Patterns across Race and Ethnicity," Opportunity and Inclusive Growth Institute Working Papers 095, Federal Reserve Bank of Minneapolis.
    • Handle: RePEc:fip:fedmoi:98595
    DOI: 10.21034/iwp.95
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    References listed on IDEAS

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    Cited by:

    1. Maggie R. Jones & Adam Bee & Amanda Eng & Kendall Houghton & Nikolas Pharris-Ciurej & Sonya R. Porter & Jonathan Rothbaum & John Voorheis, 2024. "Mobility, Opportunity, and Volatility Statistics (MOVS): Infrastructure Files and Public Use Data," Working Papers 24-23, Center for Economic Studies, U.S. Census Bureau.

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    More about this item

    Keywords

    Income inequality; Gender wage gap; Race and ethnicity; Granular income statistics;
    All these keywords.

    JEL classification:

    • D10 - Microeconomics - - Household Behavior - - - General
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • J15 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination
    • E20 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - General (includes Measurement and Data)
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts

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